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Molecular geometry optimization with a genetic algorithm

D. M. Deaven·K. M. Ho
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Abstract

We present a method for reliably determining the lowest energy structure of an atomic cluster in an arbitrary model potential. The method is based on a genetic algorithm, which operates on a population of candidate structures to produce new candidates with lower energies. Our method dramatically outperforms simulated annealing, which we demonstrate by applying the genetic algorithm to a tight-binding model potential for carbon. With this potential, the algorithm efficiently finds fullerene cluster structures up to ${\rm C}_{60}$ starting from random atomic coordinates.

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D. M. Deaven, K. M. Ho. 1995-06-16. Molecular geometry optimization with a genetic algorithm. https://doi.org/10.1103/physrevlett.75.288

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